Publications of M.Sc Mikail Yayla
2023
- Robust and Tiny Binary Neural Networks using Gradient-based Explainability Methods.
Muhammad Sabih, Mikail Yayla, Frank Hannig, Jürgen Teich, Jian-Jia Chen
EuroMLSys'23 (accepted for publication) - HW/SW Codesign for Approximation-Aware Binary Neural Networks.
Abhilasha Dave, Fabio Frustaci, Fanny Spagnolo, Mikail Yayla, Jian-Jia Chen, Hussam Amrouch
IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS) - Robust and Efficient Machine Learning for Emerging Resource-Constrained Embedded Systems (abstract, poster)
Mikail Yayla, Hussam Amrouch, Jian-Jia Chen
Poster Presentation for PhD Forum (DATE'23 and VTS'23) - Global by Local Thresholding in Binarized Neural Networks for Efficient Crossbar Accelerator Design.
Mikail Yayla, Fabio Frustaci, Fanny Spagnolo, Jian-Jia Chen, Hussam Amrouch
(under review) - HEP-BNN: A Framework for Finding Low-Latency Execution Configurations of BNNs on Heterogenerous Multiprocesser Platforms.
Leonard David Bereholschi, Ching-Chi Lin, Mikail Yayla, Jian-Jia Chen
AccML@HiPEAC'23: 5th Workshop on Accelerated Machine Learning
2022
- TREAM: A Tool for Evaluating Error Resilience of Tree-based Models using Approximate Memory.
Mikail Yayla, Zahra Valipour Dehnoo, Mojtaba Masoudinejad, and Jian-Jia Chen
SAMOS XXII International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation - Memory-Efficient Training of Binarized Neural Networks on the Edge.
Mikail Yayla and Jian-Jia Chen
Design Automation Conference (DAC'22) - Reliable Binarized Neural Networks on Unreliable Beyond von-Neumann Architecture.
Mikail Yayla, Simon Thomann, Sebastian Buschjäger, Katharina Morik, Jian-Jia Chen, and Hussam Amrouch
IEEE Transactions on Curcuits and Systems I (TCAS-I) - Deep Learning Based Driver Model and Fault Detection for Automated Racecar System Testing.
Yousef Abdulhamed, Christoph Schaefer, Mikail Yayla, Ching-Chi Lin, Jian-Jia Chen
European Automotive Reliability, Test and Safety (eARTS), DATE'22 Workshop
2021
- FeFET-based Binarized Neural Networks Under Temperature-dependent Bit Errors.
Mikail Yayla, Sebastian Buschjäger, Aniket Gupta, Jian-Jia Chen, Jörg Henkel, Katharina Morik, Kuan-Hsun Chen, Hussam Amrouch.
IEEE Transactions on Computers (TC) - Binarized SNNs: Efficient and Error-Resilient Spiking Neural Networks through Binarization.
Ming-Liang Wei, Mikail Yayla, Shu-Yin Ho, Jian-Jia Chen, Chia-Lin Yang, Hussam Amrouch.
International Conference On Computer Aided Design (ICCAD'21) - Universal Approximation Theorems for Fully Connected Binarized Neural Networks.
Mikail Yayla, Mario Günzel, Burim Ramosaj, Jian-Jia Chen.
CoRR abs/2102.02631 - Bit Error Tolerance Metrics for Binarized Neural Networks.
Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler and Mikail Yayla.
SLOHA (DATE'21 Workshop) - FeFET and NCFET for Future Neural Networks: Visions and Opportunities.
Mikail Yayla, Kuan-Hsun Chen, Georgios Zervakis, Jörg Henkel, Jian-Jia Chen and Hussam Amrouch.
In Design, Automation and Test in Europe Conference (DATE'21), Special Session - Margin-Maximization in Binarized Neural Networks for Optimizing Bit Error Tolerance.
Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler and Mikail Yayla.
In Design, Automation and Test in Europe Conference (DATE'21), Best Paper Candidate
2020
- Software-Based Memory Analysis Environments for In-Memory Wear-Leveling.
Christian Hakert, Kuan-Hsun Chen, Mikail Yayla, Georg von der Brüggen, Sebastian Bloemeke and Jian-Jia Chen.
In 25th Asia and South Pacific Design Automation Conference ASP-DAC 2020, Invited Paper - Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks.
Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen, Mario Günzel, Christian Hakert, Katharina Morik, Rodion Novkin, Lukas Pfahler and Mikail Yayla.
CoRR abs/2002.00909
2019
- Stack Usage Analysis for Efficient Wear Leveling in Non-Volatile Main Memory Systems.
Christian Hakert, Mikail Yayla, Kuan-Hsun Chen, Georg von der Brüggen, Jian-Jia Chen, Sebastian Buschjäger, Katharina Morik, Paul R. Genssler, Lars Bauer, Hussam Amrouch and Jörg Henkel.
In 1st ACM/IEEE Workshop on Machine Learning for CAD (MLCAD) - Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited Platforms.
Mikail Yayla, Anas Toma, Kuan-Hsun Chen, Lenssen, Victoria Shpacovitch, Roland Hergenröder, Frank Weichert and Jian-Jia Chen.
Journal of Sensors 19 4318 - Resource-Efficient Nanoparticle Classification Using Frequency Domain Analysis.
Mikail Yayla, Anas Toma, Jan Eric Lenssen, Victoria Shpacovitch, Kuan-Hsun Chen, Frank Weichert and Jian-Jia Chen.
In BVM'19 Workshop
2018
- Fault Tolerance on Control Applications: Empirical Investigations of Impacts from Incorrect Calculations.
Mikail Yayla, Kuan-Hsun Chen and Jian-Jia Chen.
In 4th Workshop on Emerging Ideas and Trends in Engineering of Cyber-Physical Systems (EITEC'18@CPSWEEK)
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